Non-genetic causes of autism are likely to involve multiple intermediary steps and form a complex pathophysiologic web rather than a single direct pathway. Few rigorous investigations of environmental factors that alter risk for this condition are currently underway and fewer still take into consideration complicated mechanisms of disease. We propose a study of maternal metabolic conditions characterized by systemic inflammation and insulin resistance as exposures in a pathway resulting in enhanced autism risk. Because most of the predictors are uncommon and the outcome is rare, a creative strategy is needed for an affordable study design using prospectively-collected data in large populations. Our use of four linked administrative data systems related to the massive 17-year California birth cohort will give us a sample size large enough to allow us to study both rare outcomes and rare maternal clinical exposures, thereby providing a means for validation and expansion of hypotheses generated through case-control methodology. This project will efficiently address novel hypotheses focused on the gestational environment in which the organism develops from blastocyst to neonate. The fetus is exquisitely dependent on maternal physiology to support and sustain it through the provision of nutrients, oxygen, hormonal regulation, immune surveillance, and waste disposal. Aberrations in the maternal ecosystem, deficits or imbalances of any sort in circulatory, immunologic or metabolic functional capacities, have the ability to disrupt fetal growth and development. Even subtle changes in the maternal environment can alter the flow of instructional information that regulates fetal development, including neurocognitive maturation. In recent years, industrialized countries have experienced widespread and substantial increases in adult body mass and certain accompanying metabolic conditions, such as diabetes, hypertension and lipid disorders. A growing body of evidence suggests that these conditions, when present during pregnancy, can influence neurodevelopment in the offspring in both subtle and profound ways. Thus, a large population-based examination of maternal metabolic conditions as risk factors for autism using a novel set of linkages of large population-based administrative databases has the potential to dramatically alter our conceptualization of neurodevelopment and move the field towards a more holistic understanding of its relationship to biologic systems other than the brain. This project therefore addresses maternal conditions related to systemic inflammation and insulin resistance as risks for childhood autism.